62 resultados para Process modelling


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Services based around complex engineering equipment and systems provide substantial challenges in both the long-term management of the equipment and the need for guaranteed delivery of the related service. One of the challenges for an organisation providing these services is the management of the information that is required to design, deliver and subsequently assess the success of the service. To assist in this process this paper develops a model for capturing, organising and assessing information requirements for these Complex Engineering Services in which information required to support key decisions in the life cycle of the service is identified. The model – referred to as The 12-Box Model for Service Information Requirements – is embedded in a three-phase procedure for providing an assessment of information requirements of a service contract which also provides insight into the capabilities of available information systems in supporting the contract. An illustrative example examining service information in an aircraft availability contract is used to demonstrate the use of the 12-Box Model and associated assessment procedure.

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Background: There is an increasing recognition that modelling and simulation can assist in the process of designing health care policies, strategies and operations. However, the current use is limited and answers to questions such as what methods to use and when remain somewhat underdeveloped. Aim. The aim of this study is to provide a mechanism for decision makers in health services planning and management to compare a broad range of modelling and simulation methods so that they can better select and use them or better commission relevant modelling and simulation work. Methods. This paper proposes a modelling and simulation method comparison and selection tool developed from a comprehensive literature review, the research team's extensive expertise and inputs from potential users. Twenty-eight different methods were identified, characterised by their relevance to different application areas, project life cycle stages, types of output and levels of insight, and four input resources required (time, money, knowledge and data). Results: The characterisation is presented in matrix forms to allow quick comparison and selection. This paper also highlights significant knowledge gaps in the existing literature when assessing the applicability of particular approaches to health services management, where modelling and simulation skills are scarce let alone money and time. Conclusions: A modelling and simulation method comparison and selection tool is developed to assist with the selection of methods appropriate to supporting specific decision making processes. In particular it addresses the issue of which method is most appropriate to which specific health services management problem, what the user might expect to be obtained from the method, and what is required to use the method. In summary, we believe the tool adds value to the scarce existing literature on methods comparison and selection. © 2011 Jun et al.

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Change propagates, potentially affecting many aspects of a design and requiring much rework to implement. This article introduces a cross-domain approach to decompose a design and identify possible change propagation linkages, complemented by an interactive tool that generates dynamic checklists to assess change impact. The approach considers the information domains of requirements, functions, components, and the detail design process. Laboratory experiments using a vacuum cleaner suggest that cross-domain modelling helps analyse a design to create and capture the information required for change prediction. Further experiments using an electronic product show that this information, coupled with the interactive tool, helps to quickly and consistently assess the impact of a proposed change. © 2012 Springer-Verlag London Limited.

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Computer modelling approaches have significant potential to enable decision-making about various aspects of responsive manufacturing. In order to understand the system prior to the selection of any responsiveness strategy, multiple process segments of organisations need to be modelled. The article presents a novel systematic approach for creating coherent sets of unified enterprise, simulation and other supporting models that collectively facilitate responsiveness. In this approach, enterprise models are used to explicitly define relatively enduring relationships between (i) production planning and control (PPC) processes, that implement a particular strategy and (ii) process-oriented elements of production systems, that are work loaded by the PPC processes. Coherent simulation models, can in part be derived from the enterprise models, so that they computer execute production system behaviours. In this way, time-based performance outcomes can be simulated; so that the impacts of alternative PPC strategies on the planning and controlling historical or forecasted patterns of workflow, through (current and possible future) production system models, can be analysed. The article describes the unified modelling approach conceived and its application in a furniture industry case study small and medium enterprise (SME). Copyright © 2010 Inderscience Enterprises Ltd.

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The aim of this research is to provide a unified modelling-based method to help with the evaluation of organization design and change decisions. Relevant literature regarding model-driven organization design and change is described. This helps identify the requirements for a new modelling methodology. Such a methodology is developed and described. The three phases of the developed method include the following. First, the use of CIMOSA-based multi-perspective enterprise modelling to understand and capture the most enduring characteristics of process-oriented organizations and externalize various types of requirement knowledge about any target organization. Second, the use of causal loop diagrams to identify dynamic causal impacts and effects related to the issues and constraints on the organization under study. Third, the use of simulation modelling to quantify the effects of each issue in terms of organizational performance. The design and case study application of a unified modelling method based on CIMOSA (computer integrated manufacturing open systems architecture) enterprise modelling, causal loop diagrams, and simulation modelling, is explored to illustrate its potential to support systematic organization design and change. Further application of the proposed methodology in various company and industry sectors, especially in manufacturing sectors, would be helpful to illustrate complementary uses and relative benefits and drawbacks of the methodology in different types of organization. The proposed unified modelling-based method provides a systematic way of enabling key aspects of organization design and change. The case company, its relevant data, and developed models help to explore and validate the proposed method. The application of CIMOSA-based unified modelling method and integrated application of these three modelling techniques within a single solution space constitutes an advance on previous best practice. Also, the purpose and application domain of the proposed method offers an addition to knowledge. © IMechE 2009.

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There is an increasing demand for optimising complete systems and the devices within that system, including capturing the interactions between the various multi-disciplinary (MD) components involved. Furthermore confidence in robust solutions is esential. As a consequence the computational cost rapidly increases and in many cases becomes infeasible to perform such conceptual designs. A coherent design methodology is proposed, where the aim is to improve the design process by effectively exploiting the potential of computational synthesis, search and optimisation and conventional simulation, with a reduction of the computational cost. This optimization framework consists of a hybrid optimization algorithm to handles multi-fidelity simulations. Simultaneously and in order to handles uncertainty without recasting the model and at affordable computational cost, a stochastic modelling method known as non-intrusive polynomial chaos is introduced. The effectiveness of the design methodology is demonstrated with the optimisation of a submarine propulsion system.

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A boundary integral technique has been developed for the numerical simulation of the air flow for the Aaberg exhaust system. For the steady, ideal, irrotational air flow induced by a jet, the air velocity is an analytical function. The solution of the problem is formulated in the form of a boundary integral equation by seeking the solution of a mixed boundary-value problem of an analytical function based on the Riemann-Hilbert technique. The boundary integral equation is numerically solved by converting it into a system of linear algebraic equations, which are solved by the process of the Gaussian elimination. The air velocity vector at any point in the solution domain is then computed from the air velocity on the boundary of the solution domains.

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Gaussian processes are gaining increasing popularity among the control community, in particular for the modelling of discrete time state space systems. However, it has not been clear how to incorporate model information, in the form of known state relationships, when using a Gaussian process as a predictive model. An obvious example of known prior information is position and velocity related states. Incorporation of such information would be beneficial both computationally and for faster dynamics learning. This paper introduces a method of achieving this, yielding faster dynamics learning and a reduction in computational effort from O(Dn2) to O((D - F)n2) in the prediction stage for a system with D states, F known state relationships and n observations. The effectiveness of the method is demonstrated through its inclusion in the PILCO learning algorithm with application to the swing-up and balance of a torque-limited pendulum and the balancing of a robotic unicycle in simulation. © 2012 IEEE.

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In the field of vibration-based damage detection of concrete structures efficient damage models are needed to better understand changes in the vibration properties of cracked structures. These models should quantitatively replicate the damage mechanisms in concrete and easily be used as damage detection tools. In this paper, the flexural cracking behaviour of plain concrete prisms subject to monotonic and cyclic loading regimes under displacement control is tested experimentally and modelled numerically. Four-point bending tests on simply supported un-notched prisms are conducted, where the cracking process is monitored using a digital image correlation system. A numerical model, with a single crack at midspan, is presented where the cracked zone is modelled using the fictitious crack approach and parts outside that zone are treated in a linear-elastic manner. The model considers crack initiation, growth and closure by adopting cyclic constitutive laws. A multi-variate Newton-Raphson iterative solver is used to solve the non-linear equations to ensure equilibrium and compatibility at the interface of the cracked zone. The numerical results agree well with the experiments for both loading scenarios. The model shows good predictions of the degradation of stiffness with increasing load. It also approximates the crack-mouth-opening-displacement when compared with the experimental data of the digital image correlation system. The model is found to be computationally efficient as it runs full analysis for cyclic loading in less than 2. min, and it can therefore be used within the damage detection process. © 2013 Elsevier Ltd.

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Purpose: Although business models that deliver sustainability are increasingly popular in the literature, few tools that assist in sustainable business modelling have been identified. This paper investigates how businesses might create balanced social, environmental and economic value through integrating sustainability more fully into the core of their business. A value mapping tool is developed to help firms create value propositions better suited for sustainability. Design/methodology/approach: In addition to a literature review, six sustainable companies were interviewed to understand their approaches to business modelling, using a case study approach. Building on the literature and practice, a tool was developed which was pilot tested through use in a workshop. The resulting improved tool and process was subsequently refined through use in 13 workshops. Findings: A novel value mapping tool was developed to support sustainable business modelling, which introduces three forms of value (value captured, missed/destroyed or wasted, and opportunity) and four major stakeholder groups (environment, society, customer, and network actors). Practical implications: This tool intends to support business modelling for sustainability by assisting firms in better understanding their overall value proposition, both positive and negative, for all relevant stakeholders in the value network. Originality/value: The tool adopts a multiple stakeholder view of value, a network rather than firm centric perspective, and introduces a novel way of conceptualising value that specifically introduces value destroyed or wasted/ missed, in addition to the current value proposition and new opportunities for value creation. © Emerald Group Publishing Limited.

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We present some recent developments in automated computational modelling with an emphasis on solid mechanics applications. The automation process permits an abstract mathematical model of a physical problem to be translated into computer code rapidly and trivially, and can lead to computer code which is faster than hand-written and optimised code. Crucial to the approach is ensuring that mathematical abstractions inherent in the mathematical model are inherited by the software library. © Springer Science+Business Media B.V. 2008.

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Results of numerical investigations of the wet steam flow in a three stage low pressure steam turbine test rig are presented. The test rig is a scale model of a modern steam turbine design and provides flow measurements over a range of operating conditions which are used for detailed comparisons with the numerical results. For the numerical analysis a modern CFD code with user defined models for specific wet steam modelling is used. The effect of different theoretical models for nucleation and droplet growth are examined. It is shown that heterogeneous condensation is highly dependent on steam quality and, in this model turbine with high quality steam, a homogeneous theory appears to be the best choice. The homogeneous theory gives good agreement between the test rig traverse measurements and the numerical results. The differences in the droplet size distribution of the three stage turbine are shown for different loads and modelling assumptions. The different droplet growth models can influence the droplet size by a factor of two. An estimate of the influence of unsteady effects is made by means of an unsteady two-dimensional simulation. The unsteady modelling leads to a shift of nucleation into the next blade row. For the investigated three stage turbine the influence due to wake chopping on the condensation process is weak but to confirm this conclusion further investigations are needed in complete three dimensions and on turbines with more stages. Copyright © 2011 by ASME.

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An accurate description of atomic interactions, such as that provided by first principles quantum mechanics, is fundamental to realistic prediction of the properties that govern plasticity, fracture or crack propagation in metals. However, the computational complexity associated with modern schemes explicitly based on quantum mechanics limits their applications to systems of a few hundreds of atoms at most. This thesis investigates the application of the Gaussian Approximation Potential (GAP) scheme to atomistic modelling of tungsten - a bcc transition metal which exhibits a brittle-to-ductile transition and whose plasticity behaviour is controlled by the properties of $\frac{1}{2} \langle 111 \rangle$ screw dislocations. We apply Gaussian process regression to interpolate the quantum-mechanical (QM) potential energy surface from a set of points in atomic configuration space. Our training data is based on QM information that is computed directly using density functional theory (DFT). To perform the fitting, we represent atomic environments using a set of rotationally, permutationally and reflection invariant parameters which act as the independent variables in our equations of non-parametric, non-linear regression. We develop a protocol for generating GAP models capable of describing lattice defects in metals by building a series of interatomic potentials for tungsten. We then demonstrate that a GAP potential based on a Smooth Overlap of Atomic Positions (SOAP) covariance function provides a description of the $\frac{1}{2} \langle 111 \rangle$ screw dislocation that is in agreement with the DFT model. We use this potential to simulate the mobility of $\frac{1}{2} \langle 111 \rangle$ screw dislocations by computing the Peierls barrier and model dislocation-vacancy interactions to QM accuracy in a system containing more than 100,000 atoms.